Computer Vision: Models, Learning, and Inference
Overview & Synopsis
With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision.
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Document Information
| Document Title | Computer Vision: Models, Learning, and Inference |
|---|---|
| Author / Organization | Simon J. D. Prince |
| Subject & Discipline | Computer and Machine Vision, Artificial Intelligence, Machine Learning, and Logic Programming, Probability, Stochastic Process, Queueing Theory, etc., Digital Signal Processing (DSP), Sound and Imaging Processing, Human-Computer Interaction |
| Categories | Computer and Machine Vision |
| ISBN | 1107011795 |
| Resource Verification | Verification pending |
| Alternative Mirrors & Links | |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Language | ENGLISH |
| Catalog ID | DOC-11821 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |
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